Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T00:01:36.993633Z
Paper Citation Record · LEDGER
As of 22 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 1 inbound Pith citation observation for arXiv:2505.03096.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T00:01:36.993633Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-08T08:20:33.374650Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T20:41:11.495121Z
43 of 43 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation f1b325a6-098b-4010-bfdc-f43ee0846451 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Copilot
Reference 1
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation a89fd123-70e2-4642-b95f-60d0df10d9f5 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Google AI for Developers
Reference 2
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation b4d7bbf7-15c1-46d0-a2ce-5e4dc0eb1e13 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering ChatGPT
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation d8e59f97-58ec-4d60-8c89-b15d56e63aab · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Attention is all you need,
Reference 4
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cfef33c1-71b8-4c5f-a803-ab9b4402edf2 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Exploring the limits of transfer learning with a unified text-to-text transformer,
Reference 5
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b4c3ea5-8927-489a-a7e5-465412683a78 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering WebGPT: Browser-assisted question-answering with human feedback
Reference 6
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 209bac15-10d6-4e2d-8199-9dbea5ad8c73 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Examining zero-shot vulnerability repair with large language models,
Reference 7
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation c01dd0a6-c10a-4eb3-9b43-05180e35ac3e · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity
Reference 8
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a50f9b14-8ae1-4bd3-a642-6272653e2c6e · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Why Agents are the next frontier of generative AI,
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation de634598-619c-44f8-b1f5-346fa76544aa · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering LLM Multi-Agent Systems: Challenges and Open Problems
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1f7c1f0b-a794-42b3-b6cf-dc281327d6cb · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Exploring Autonomous Agents through the Lens of Large Language Models: A Review
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 539db196-4d33-4560-b1ec-13f8459aa9bc · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Why Solving Multi-agent Path Finding with Large Language Model has not Succeeded Yet
Reference 12
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 81c47e64-9923-416a-8a8e-3ff06d45b709 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework
Reference 13
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ca48abb6-3efb-4e64-97af-25132666a057 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Chaos engineering for resilience assessment of digital twins,
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 86521bf6-4b18-4f5d-802a-dad4dd2653e3 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Chaos engineering,
Reference 15
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 5177c1c6-4455-43a5-a90d-69f46d547a4a · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Chaos engineering of ethereum blockchain clients,
Reference 16
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 09fb542f-8ee8-4277-8baa-ee842bd92650 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Chaos engineering: At the age of AI and ML,
Reference 17
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 14be2b47-d0f0-45ee-836f-41f0bddc1137 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering The role of theory and theorising in design science research,
Reference 18
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation d844bc32-77c4-4d58-a074-0470334628fe · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Action research,
Reference 19
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3468ed4b-091a-4b31-8038-4cbfd7ef2a97 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering A Survey on Evaluating Large Language Models in Code Generation Tasks
Reference 20
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b6e50d4e-4456-4ded-8237-462db1ce3e8b · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering LLMs for code: The potential, prospects, and problems,
Reference 21
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 9cd1e85c-1fac-47bb-88ce-fbc9e4c3fa59 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Weaknesses in LLM- generated code for embedded systems networking,
Reference 22
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation cb8c95a0-e8de-4dd3-9a1b-a44096913c60 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering A survey on LLM- based multi-agent systems: workflow, infrastructure, and challenges,
Reference 23
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b326f425-f182-4d23-a699-cceb6f8db6b4 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering System for systematic literature review using multiple AI agents: Concept and an empirical evaluation,
Reference 24
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ea50fba8-1e3e-4aa2-852f-e2a96463e830 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Synchromesh: Reliable code generation from pre-trained language models
Reference 25
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4e6e804d-4a9f-4cfd-b0f5-0bfc44740b87 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Assessing the quality of GitHub Copilot’s code generation,
Reference 26
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 23076143-390a-424e-920c-1fc0a84eb96e · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Can LLM replace Stack Overflow? a study on robustness and reliability of large language model code genera- tion,
Reference 27
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 41b9039c-f402-4c36-9ab9-b58b7dbd5daf · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Improving alignment and robustness with circuit breakers,
Reference 28
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation da622a7a-20ab-45e3-81f1-c401a9a211cc · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Robust LLM safeguarding via refusal feature adversarial training
Reference 29
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e84482ec-b5f9-4820-b804-a12385b4a798 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering NetSafe: Exploring the Topological Safety of Multi-agent Networks
Reference 30
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4fa77986-2553-4378-9c21-f02dd9e673f3 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Trustagent: Towards safe and trustworthy LLM-based agents through agent constitution,
Reference 31
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 87cc247b-89a1-4380-abe6-d3bd111b2917 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Cut the Crap: An Economical Communication Pipeline for LLM-based Multi-Agent Systems
Reference 32
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 61987db6-66a7-4dcc-a541-1bb5d4630925 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Chaos engineering in machine learning: Embracing the unpredictable to enhance system robustness,
Reference 33
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 4204cb57-6754-47c0-8fd5-0efda3d61f8f · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Introducing chaos engineering to machine learning deploy- ments,
Reference 34
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation faa3f6af-7db7-4e62-91d1-56d4acfce403 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Embracing disruption: Applying machine learning to chaos engineering,
Reference 35
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 42935381-556a-4efe-abb2-64c48cb961da · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering An empirical investigation of the acceptance of chaos engineering,
Reference 36
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 59d59a09-d7d1-47b2-a026-b5149113b02f · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Harnessing chaos: The role of chaos engineering in cloud applications and impacts on site reliability engineering,
Reference 37
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 0006e531-6e72-4816-9e34-fa15ceb0b2ca · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering A chaos engineering system for live analysis and falsification of exception- handling in the jvm,
Reference 38
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation ff4fea20-728d-4e12-8ddc-313c18d1aafe · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering The design science paradigm as a frame for empirical software engineering,
Reference 39
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 3729c79d-0918-4358-9c4a-8a127bdc3024 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering How software engineering research aligns with design science: a review,
Reference 40
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 7bd2f4ec-7c54-42c9-b870-cd27e637c067 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Managing risk in software process improvement: an action research approach,
Reference 41
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 036c5580-bfe7-41a5-8d74-8f00c3cd49ba · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Data quality certification using iso/iec 25012: Industrial experiences,
Reference 42
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 6addc7a7-6f6f-441c-a333-ce534a320aa4 · outbound
Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering Action research as research methodology in software engineering,
Reference 43
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 6102797d-da37-4dc8-a808-98bbaa159315 · inbound
Code Broker: A Multi-Agent System for Automated Code Quality Assessment Assessing and Enhancing the Robustness of LLM-based Multi-Agent Systems Through Chaos Engineering
Reference 25
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.